Tutorial 2: Use of Data

Question 1

Define disease.

Answer 1

Symptoms, signs – diagnosis. Bio-medical perspective.

Question 2

Define illness.

Answer 2

Ideas, concerns, expectations – experience. Patients perspective.

Question 3

List factors affecting uptake of care.

Answer 3

• Lay referral: going from family → community → traditional/cultural healing → medical system
• Sources of information: Peers, family, internet, TV etc.
• Medical factors: new symptoms, visible symptoms, increasing severity, duration.
• Non-medical factors: crisis/psychological state, peer pressure (spouse/friends), ICE, social class, economic, environmental, cultural, ethnic, age, gender, media.
• Issues:
  ○ Patient believe self to be healthy: physically fit, doesn’t want to use tablets
  ○ Doctor: rationale behind performing additional investigations, educate self of concerns regarding patient’s health

Question 4

Patient has irregularly irregular pulse. Atrial fibrillation is suspected. What investigations would you perform to confirm diagnosis?

Answer 4

• ECG: shows absent P waves, irregularly irregular QRS complexes.
• Urea & electrolytes (problems with kidney function)
• Thyroid function tests (TFTS): rule out hyperthyroidism
• Full blood count (FBC): to rule out anaemia.
• Can also do echocardiogram (assess the structure and function of the heart and valves to rule out other heart-related problems); Holter monitor.

Question 5

What are the three main aims of epidemiology?

Answer 5

1. Description: To describe the amount and distribution of disease in human populations.
2. Explanation: To elucidate the natural history and identify aetiological factors for disease usually by combining epidemiological data with data from other disciplines such as biochemistry, occupational health and genetics.
3. Disease control: To provide the basis on which preventive measures, public health practices and therapeutic strategies can be developed,
   implemented, monitored and evaluated for the purposes of disease control.
   Epidemiology compares groups (study population) to find: aetiological clues, scope of prevention, and identify high risk groups.

Question 6

What is the difference between clinical medicine and epidemiology?

Answer 6

Clinical medicine deals with the individual patient, epidemiology deals with populations. Distinction important in order to formulate a hypothesis about disease and risk. Normally done by calculating ratio:
Numerator/Denominator = Events/Population at risk
This ratio converted into rate by expressing it in terms of a specified time period (eg, per year) and a notional ‘at risk’ population of 10n (eg, %; per 1000; per 100,000).

Question 7

Define relative risk.

Answer 7

Measure of the strength of an association between a suspected risk factor and the disease under study.
Relative risk (RR) = 	incidence of disease in exposed group/incidence of disease in unexposed group.

Question 8

What are the sources of epidemiological data?

Answer 8

Mortality data
Hospital and clinical activity statistics
Reproductive health statistics
Infectious disease statistics
Cancer statistics
Accident statistics
General practice morbidity statistics
Health and household surveys
Labour force surveys
Social security statistics
Drug misuse databases
Expenditure data from NHS

Question 9

What is health literacy?

Answer 9

Having knowledge, skills, understanding & confidence to use health information in order to be active partner in care, and to navigate healthcare systems.

Question 10

What is CHA2DS2-VASc score?

Answer 10

Clinical prediction rules for estimating the risk of (thromboembolic) stroke in patients with non-rheumatic atrialfibrillation (AF). Score is used to determine whether or not treatment is required with anticoagulation therapy or antiplatelet therapy.
High score = greater risk of stroke & vice versa.
Takes into account age, sex, and history of CHF, hypertension, diabetes, vascular disease, TIA/stroke/thromboembolism.

Question 11

When prescribing warfarin what is needed to be taken into account?

Answer 11

Bleeding risk (use HAS-BLED score) vs long-term consequences of stroke.

Question 12

Compare NOAC’s with warfarin.

Answer 12

NOAC’s do not require regular blood test monitoring like warfarin, this appeals to most patients.
However, they are more expensive, and are not easily reversed like warfarin (vitamin K used) in case of bleeding.

Question 13

What are SIGN guidelines and what are they intended for?

Answer 13

The guidelines are based on a systematic review of the scientific literature and are aimed at aiding the translation of new knowledge into action. The guidelines are intended to:
- Help understand medical evidence and use it to make decisions about healthcare.
- Reduce variations in practice and ensure patients get the best care available, no matter where they live.
- Improve healthcare by focusing on patient-important outcomes.
SIGN guidelines also provide rated evidence.

Question 14

List types of studies.

Answer 14

Descriptive studies.
Analytic studies: Cross-sectional studies, Case control studies, Cohort studies.
Trials: randomised controlled trial.

Question 15

Define descriptive studies and give limitations and advantages.

Answer 15

Describe the amount and distribution of a disease in a given population. Follow the time, place, person framework.
Does not provide definitive conclusion about disease causation but can provide insight about possible risk factors and aetiologies.
Cheap, quick and give a valuable initial overview of a problem.

Question 16

What are descriptive studies useful in?

Answer 16

• Identifying emerging public health problems through monitoring and surveillance of disease patterns.
• Signalling the presence of effects worthy of further investigation.
• Assessing the effectiveness of measures of prevention and control (eg, screening programmes).
• Assessing needs for health services and service planning.
• Generating hypotheses about disease aetiology.

Question 17

What are cross-sectional studies? Comment on advantages & disadvantages.

Answer 17

Observational study design (observations are made at a single point in time). Outcome and the exposures are measured in the study participants at the same time. Conclusions are drawn about the relationship between diseases (or other health-related characteristics) and other variables of interest
Used for population-based surveys, estimating prevalence in studies, calculating odds ratio, and disease frequency.
Advantages: Can be done quickly, inexpensive, and can be used to plan cohort studies.
Disadvantages: cannot infer causation as 1-time measurement performed, and can be biased.

Question 18

Define case-control studies. Results from the study are expressed as what?

Answer 18

Two groups of people are compared: a group of individuals who have the disease of interest are identified (cases), and a group of individuals who do not have the disease (controls).
Data gathered about exposure to aetiological factor of interest. Average exposure compared to identify significant differences, and any factors that elevate or reduce risk of the disease.
Results expressed as odds ratio, relative risk or p values.

Question 19

Define cohort studies.

Answer 19

Data on exposure are collected from a group of people who do not have the disease under study. The group is then followed through time until a sufficient number have developed the disease to allow analysis. Original group divided into subgroups based on exposure initially and then these groups are compared.
Results expressed as relative risks, with confidence intervals or p values.

Question 20

What are advantages or limitations of cohort studies?

Answer 20

Advantages: Cohort studies allow the calculation of cumulative incidence, allowing for differences in follow up time.
Limitations: costly, and greater chance of losing subjects to follow-up based on the long time period over which cohorts are typically followed.

Question 21

Define trials.

Answer 21

Trials are experiments used to test ideas about aetiology or to evaluate interventions. The “randomised controlled trial” is the definitive method of assessing any new treatment in medicine.
Two groups at risk of developing disease are taken. One is the intervention group from which causative factor is removed/neutralised. No alteration is made to 2nd control group. Data collected from both groups are relative risk is calculated. The aim is to determine whether modification of the factor (removing, reducing or increasing exposure) alters the incidence of the disease.
In a trial of a new treatment, the underlying design is the same: the intervention group receive the new therapy, the control group receive the current standard therapy (or a placebo) and the treatment outcomes (eg, reduction in symptoms) are compared in the two groups.

Question 22

What factors are needed to be considered while interpreting results?

Answer 22

1. Standardisation
2. Standardised mortality ratio
3. Quality of Data: ensure data is trustworthy.
4. Case definition
5. Coding and classification
6. Ascertainment

Question 23

Define standardisation.

Answer 23

A set of techniques used to remove (or adjust for) the effects of differences in age or other confounding variables, when comparing two or more populations.

Question 24

Define standardised mortality ratio.

Answer 24

Standardised death rate converted to ratio, e.g. standard is 100, 120 means 20% more death than expected.

Question 25

What is the purpose of case definition?

Answer 25

To decide whether an individual has the condition of interest or not. Differences in incidence of disease over time or in different populations may be artefact, due to differences in case definition, rather than differences in true incidence.

Question 26

What is the importance of coding and classification?

Answer 26

Important to know what the rules are for converting clinical information into a code while storing data (e.g. death certificates). Sometimes when rules change it appears that a disease has become more common, or less common, when in fact it has just been coded under a new heading.

Question 27

Define ascertainment.

Answer 27

Completeness of data. Higher incidence rates might be due to one country looking for it harder than the other one so making sure data is complete from each country will allow for better comparison if needed e.g. COVID-19 was tested more in South Korea so appeared to have higher cases as oppose to other countries who didn’t test as much.

Question 28

Define bias.

Answer 28

Bias is any trend in the collection, analysis, interpretation, publication or review of data that can lead to conclusions that are systematically different from the truth.

Question 29

List different types of biases.

Answer 29

Selection Bias
Information Bias
Follow up Bias
Systematic Error
Publication bias

Question 30

Define selection bias.

Answer 30

Occurs when the study sample is not truly representative of the whole study population about which conclusions are to be drawn. For example, in a randomised controlled trial of a new drug, subjects should be allocated to the intervention (study) group and control group using a random method. If certain types of people (eg, older, more ill) were deliberately allocated to one of these groups then the results of the trial would reflect these differences, not just the effect of the drug.

Question 31

How does information bias arise?

Answer 31

Arises from systematic errors in measuring exposure or disease. For example, in a case control study, a researcher who was aware of whether the patient being interviewed was a ‘case’ or a ‘control’ might encourage cases more than controls to think hard about past exposures to the factors of interest. Any differences in exposure would then reflect the enthusiasm of the researcher as well as any true difference in exposure between the two groups.

Question 32

How does follow-up bias arise?

Answer 32

Arises when one group of subjects is followed up more assiduously than another to measure disease incidence or other relevant outcome. For example, in cohort studies, subjects sometimes move address or fail to reply to questionnaires sent out by the researchers. If greater attempts are made to trace these missing subjects from the group with greater initial exposure to a factor of interest than from the group with less exposure, the resulting relative risk would be based on a (relative) underestimate of the incidence in the less exposed group compared with the more exposed group.

Question 33

What is systematic error?

Answer 33

A form of measurement bias where there is a tendency for measurements to always fall on one side of the true value. It may be because the instrument (e.g., a blood pressure machine) is calibrated wrongly, or because of the way a person uses an instrument. This problem may occur with interviews, questionnaires etc, as well as with medical instruments.

Question 34

How does publication bias occur?

Answer 34

Occurs where positive results have a greater chance of being published (even if the quality of the study is poorer than a similar study showing negative results).

Question 35

What are confounding factors?

Answer 35

A confounding factor is one which is associated independently with both the disease and with the exposure under investigation and so distorts the relationship between the exposure and disease. In some cases the confounding factor may be the true causal factor, and not the exposure that is under consideration.
Age, sex and social class are common confounders.

Question 36

How can you deal with confounding factors?

Answer 36

Depends on particular study design:

• In trials, the process of randomisation
• Restriction of eligibility criteria to only certain kinds of study subjects .
• Subjects in different groups can be matched for likely confounding factors.
• Results can be stratified according to confounding factors.
• Results can be adjusted (using multivariate analysis techniques) to take account of suspected confounding factors.

Question 37

What is the criteria of causality?

Answer 37

Difficult to prove causation between disease and exposure so a criteria has been designed:

• Strength of association (as measured by relative risk or odds ratio).
• Consistency (repeated observation of an association in different populations under different circumstances)
• Specificity (single exposure leading to single disease)
• Temporality (the exposure comes before the disease)
• Biological gradient (dose-response relationship. As the exposure increases so does the risk of disease)
• Biological plausibility (association agrees with what is known about the biology of the disease).
• Coherence (association does not conflict with what is known about the biology of the disease)
• Analogy (another exposure-disease relationship exists that can be used as a model for current one)
• Experiment: suitably controlled experiment to prove association as causal(uncommon in human populations)

Question 38

What is the absolute criterion of causality?

Answer 38

Temporality. Failing to fulfil any of the others does not necessarily rule out a causative association.